73 citations · 129 across the 5 of their papers we have counts for
5 papers
Multi-source Domain Adaptation in the Deep Learning Era: A Systematic Survey
Sicheng Zhao, Bo Li, Colorado Reed +2
In many practical applications, it is often difficult and expensive to obtain enough large-scale labeled data to train deep neural networks to their full capability. Therefore, tra…
Micro/Nano Motor Navigation and Localization via Deep Reinforcement Learning
Yuguang Yang, Michael A. Bevan, Bo Li
Efficient navigation and precise localization of Brownian micro/nano self-propelled motor particles within complex landscapes could enable future high-tech applications involving f…
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Yuyu Zhang, Xinshi Chen, Yuan Yang +4
Markov Logic Networks (MLNs), which elegantly combine logic rules and probabilistic graphical models, can be used to address many knowledge graph problems. However, inference in ML…
Large Deviation Analysis of Function Sensitivity in Random Deep Neural Networks
Bo Li, David Saad
Mean field theory has been successfully used to analyze deep neural networks (DNN) in the infinite size limit. Given the finite size of realistic DNN, we utilize the large deviatio…
Detecting genuine multipartite correlations in terms of the rank of coefficient matrix
Bo Li, Leong Chuan Kwek, Heng Fan
We propose a method to detect genuine quantum correlation for arbitrary quantum state in terms of the rank of coefficient matrices associated with the pure state. We then derive a…